curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "twitter",
"keyword": "(\"anyone recommend\" OR \"looking for\") CRM",
"date_posted": "past_week",
"count": 25
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "reddit",
"keyword": "CRM recommendation",
"subreddit": "SaaS",
"sort_by": "relevance",
"count": 25
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "linkedin",
"keyword": "CRM",
"author_company": "Salesforce",
"date_posted": "past_week",
"count": 25
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "linkedin",
"keyword": "hiring SDR",
"include": ["reactions", "comments"],
"engagement_count": 25,
"count": 10
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"post_url": "https://www.linkedin.com/posts/janedoe_activity-123456789",
"include": ["reactions", "comments"],
"engagement_count": 50
}'
{
"total": 25,
"offset": 0,
"count": 1,
"has_next": true,
"credits_used": 1,
"results": [
{
"post_id": "1811640448000000000",
"platform": "twitter",
"url": "https://x.com/janedoe/status/1811640448000000000",
"text": "anyone got a CRM recommendation that does round-robin without the enterprise upsell?",
"created_at": "2026-07-10T14:22:03Z",
"is_repost": false,
"author_handle": "janedoe",
"author_name": "Jane Doe",
"author_bio": "Head of RevOps @ Acme",
"author_followers": 4200,
"author_verified": false,
"like_count": 8,
"comment_count": 3,
"repost_count": 0,
"view_count": 900
}
]
}
Search
Search Social Posts
Search posts on LinkedIn, Twitter/X and Reddit
POST
/
search
/
posts
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "twitter",
"keyword": "(\"anyone recommend\" OR \"looking for\") CRM",
"date_posted": "past_week",
"count": 25
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "reddit",
"keyword": "CRM recommendation",
"subreddit": "SaaS",
"sort_by": "relevance",
"count": 25
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "linkedin",
"keyword": "CRM",
"author_company": "Salesforce",
"date_posted": "past_week",
"count": 25
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "linkedin",
"keyword": "hiring SDR",
"include": ["reactions", "comments"],
"engagement_count": 25,
"count": 10
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"post_url": "https://www.linkedin.com/posts/janedoe_activity-123456789",
"include": ["reactions", "comments"],
"engagement_count": 50
}'
{
"total": 25,
"offset": 0,
"count": 1,
"has_next": true,
"credits_used": 1,
"results": [
{
"post_id": "1811640448000000000",
"platform": "twitter",
"url": "https://x.com/janedoe/status/1811640448000000000",
"text": "anyone got a CRM recommendation that does round-robin without the enterprise upsell?",
"created_at": "2026-07-10T14:22:03Z",
"is_repost": false,
"author_handle": "janedoe",
"author_name": "Jane Doe",
"author_bio": "Head of RevOps @ Acme",
"author_followers": 4200,
"author_verified": false,
"like_count": 8,
"comment_count": 3,
"repost_count": 0,
"view_count": 900
}
]
}
Search posts by keyword across platforms. Every platform returns the same
normalized post schema, so you parse LinkedIn, Twitter and Reddit results
identically. Each post carries its author — a lead you can pass to
Enrich Profile.
Credit Cost
| Mode | Credits |
|---|---|
| Posts | 1 credit per 10 posts returned |
Engagers (include) | 1 credit per 10 reactions/comments returned |
Request Body
string
default:"linkedin"
Platform to search:
linkedin, twitter, or reddit.string
Search keyword or phrase in the post content (e.g.,
"looking for a CRM"). On Twitter you can use advanced operators (OR, quoted phrases, -word).string
default:"strict"
Keyword matching mode:
strict(default) — only returns posts whose text actually contains the searched terms. Platforms match loosely by default (a keyword can appear only as a stock ticker, inside a link, or scattered across the post), so strict mode filters that noise out. Bare words are required (AND); quoted phrases are alternatives (OR).loose— returns the platform’s raw results without post-filtering.
string
Freshness of the posts:
past_24h, past_week, past_month. Mapped to each platform’s native time window.string
default:"date_posted"
Ordering:
date_posted (freshest first) or relevance (most relevant/engaged).string
Reddit only. Restrict the search to one subreddit (e.g.,
"SaaS").string
LinkedIn only. Restrict to posts by employees of a company — pass a name (auto-resolved to the company) or a numeric LinkedIn company ID.
string
LinkedIn only. Restrict to authors in an industry.
string
LinkedIn only. Restrict to authors with a job title (e.g.,
"Head of Sales").string
LinkedIn only. Restrict to a content type:
ARTICLE, VIDEO, PHOTO, DOCUMENT.integer
default:"0"
Number of results to skip for pagination (LinkedIn).
integer
default:"10"
Number of posts to return. Maximum: 100 per request.
array
Attach the people who engaged with each returned post. Any of
["reactions", "comments"]. Each post then carries a reactions and/or comments array of engagers (name, headline, profile URL) — leads you can pass to Enrich Profile. Reddit has no reactions, so only comments applies there.integer
default:"25"
Max engagers to return per type, per post, when
include is set (1–1000).string
Fetch the engagers of one specific post instead of running a keyword search. Pass a post URL; the response returns that single post with its
reactions and comments arrays (bounded by engagement_count). Use include to restrict to one type.Response
integer
Total matching posts on LinkedIn; a lower bound (enumerated so far) on Twitter/Reddit, which expose no global count — use
has_next to know if more exist.integer
Offset used for pagination.
integer
Number of results returned in this response.
boolean
Whether more results are available.
number
Credits used for this search.
array
List of posts, normalized across platforms. Same core fields everywhere; a few platform-specific extras on top.
Show post properties
Show post properties
string
Platform post ID
string
Source platform (
linkedin, twitter, reddit)string
URL of the post
string
Post text content
string
Publication date
boolean
Whether the post is a repost/retweet/reshare
string
Author handle / public identifier — pass to Enrich Profile
string
Author display name
string
Author headline/bio
integer
Author follower count (when exposed)
boolean
Whether the author is verified
integer
Likes (Twitter/LinkedIn) or upvotes (Reddit)
integer
Number of comments/replies
integer
Reposts/retweets/reshares
integer
Views (when exposed)
string
Reddit only — the subreddit
mixed
Twitter only — post language, number of quotes, and whether the post is a reply
mixed
LinkedIn only — author profile URL and picture, days since publication, and post audience (e.g.
PUBLIC)array
Present when
include contains reactions. Engagers who reacted, each with reaction_type and an author (name, headline, profile URL).array
Present when
include contains comments. Commenters, each with the comment text, created_at and an author.curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "twitter",
"keyword": "(\"anyone recommend\" OR \"looking for\") CRM",
"date_posted": "past_week",
"count": 25
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "reddit",
"keyword": "CRM recommendation",
"subreddit": "SaaS",
"sort_by": "relevance",
"count": 25
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "linkedin",
"keyword": "CRM",
"author_company": "Salesforce",
"date_posted": "past_week",
"count": 25
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"platform": "linkedin",
"keyword": "hiring SDR",
"include": ["reactions", "comments"],
"engagement_count": 25,
"count": 10
}'
curl -X POST https://api.dataforb2b.ai/search/posts \
-H "api_key: YOUR_api_key" \
-H "Content-Type: application/json" \
-d '{
"post_url": "https://www.linkedin.com/posts/janedoe_activity-123456789",
"include": ["reactions", "comments"],
"engagement_count": 50
}'
{
"total": 25,
"offset": 0,
"count": 1,
"has_next": true,
"credits_used": 1,
"results": [
{
"post_id": "1811640448000000000",
"platform": "twitter",
"url": "https://x.com/janedoe/status/1811640448000000000",
"text": "anyone got a CRM recommendation that does round-robin without the enterprise upsell?",
"created_at": "2026-07-10T14:22:03Z",
"is_repost": false,
"author_handle": "janedoe",
"author_name": "Jane Doe",
"author_bio": "Head of RevOps @ Acme",
"author_followers": 4200,
"author_verified": false,
"like_count": 8,
"comment_count": 3,
"repost_count": 0,
"view_count": 900
}
]
}